Developing
Collaborative Applications with Mobile Cloud -
A Case Study
of Speech Recognition
Yu-Shuo Chang and Shih-Hao Hung
Department of
Computer Science and Information Engineering
National
Taiwan University, Taipei, 106, Taiwan
asouchang@gmail.com, hungsh@csie.ntu.edu.tw
Abstract
While the combination of cloud
computing and mobile computing, termed mobile cloud computing,
started to show its effects recently
with many seemingly innovative smartphone applications
and cloud services surfacing to the market
today, we believe that the real potentials of mobile cloud
computing is far from been fully
explored due to several practical issues. The quality of the mobile
networks is not adequate for
delivering satisfactory user experiences via close collaboration over
mobile networks. A dynamic workload
partitioning scheme would help solve this problem, but the
distribution of computation and data
storage geographically can lead to serious security and privacy
concerns, which makes user to take
the risk of exposing the data to eavesdroppers in the middle of
the network.
Since we have yet to see
collaborative mobile cloud applications which could dynamically migrate
the workload to efficiently take
advantage of the resources in the cloud, in this paper, we present
a paradigm to guide the design of the
following: the system architecture, the principle for partitioning
applications, the method for
offloading computation, and the control policy for data access. We argue
that the proposed paradigm provides a
unified solution to the performance and privacy issues, with a
case study, a cloud-assisted speech
recognition application, to illustrate our experimental results.
Journal of Internet
Services and Information Security (JISIS), 1(1):
18-36, May 2011 [pdf]